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06/30/2023
Proximal nested sampling with data-driven priors for physical scientists
Proximal nested sampling was introduced recently to open up Bayesian mod...
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06/30/2023
Learned harmonic mean estimation of the marginal likelihood with normalizing flows
Computing the marginal likelihood (also called the Bayesian model eviden...
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03/15/2023
The Tiny Time-series Transformer: Low-latency High-throughput Classification of Astronomical Transients using Deep Model Compression
A new golden age in astronomy is upon us, dominated by data. Large astro...
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02/12/2023
Slepian Scale-Discretised Wavelets on Manifolds
Inspired by recent interest in geometric deep learning, this work genera...
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01/24/2023
Learned Interferometric Imaging for the SPIDER Instrument
The Segmented Planar Imaging Detector for Electro-Optical Reconnaissance...
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09/27/2022
Scalable and Equivariant Spherical CNNs by Discrete-Continuous (DISCO) Convolutions
No existing spherical convolutional neural network (CNN) framework is bo...
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11/24/2021
Machine learning assisted Bayesian model comparison: learnt harmonic mean estimator
We resurrect the infamous harmonic mean estimator for computing the marg...
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06/07/2021
High-dimensional Bayesian model selection by proximal nested sampling
Imaging methods often rely on Bayesian statistical inference strategies ...
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06/03/2021
Slepian Scale-Discretised Wavelets on the Sphere
This work presents the construction of a novel spherical wavelet basis d...
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05/13/2021
Paying Attention to Astronomical Transients: Photometric Classification with the Time-Series Transformer
Future surveys such as the Legacy Survey of Space and Time (LSST) of the...
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05/12/2021
Bayesian variational regularization on the ball
We develop variational regularization methods which leverage sparsity-pr...
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05/11/2021
Sparse image reconstruction on the sphere: a general approach with uncertainty quantification
Inverse problems defined naturally on the sphere are becoming increasing...
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03/05/2021
Reducing cybersickness in 360-degree virtual reality
Despite the technological advancements in Virtual Reality (VR), users ar...
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02/04/2021
Scattering Networks on the Sphere for Scalable and Rotationally Equivariant Spherical CNNs
Convolutional neural networks (CNNs) constructed natively on the sphere ...
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10/15/2020
Multiscale Optimal Filtering on the Sphere
We present a framework for the optimal filtering of spherical signals co...
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07/23/2020
Sifting Convolution on the Sphere
A novel spherical convolution is defined through the sifting property of...
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12/12/2017
Online radio interferometric imaging: assimilating and discarding visibilities on arrival
The emerging generation of radio interferometric (RI) telescopes, such a...
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11/13/2017
Uncertainty quantification for radio interferometric imaging: II. MAP estimation
Uncertainty quantification is a critical missing component in radio inte...
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11/13/2017
Uncertainty quantification for radio interferometric imaging: I. proximal MCMC methods
Uncertainty quantification is a critical missing component in radio inte...
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09/21/2016
